Research Assistant, Oulu Mining School, Faculty of Technology - Hiring in process/Finished, not possible to apply

We are now looking for

Research Assistant 

to join us for Master’s/Diploma thesis work in Oulu Mining School at the Faculty of Technology. 

The Research Assistant will support the development of a smart process optimisation framework by contributing to sensor integration, data engineering, machine learning model development, and digital twin connectivity. The role combines experimental work, computational modelling, and engineering design.

About the job

Oulu Mining School is investigating Circularity Integrated Mining solutions in the Business Finland CINTEM project.

The position focuses on advancing digitalisation in mineral processing, specifically froth flotation, through the integration of multi-sensor data acquisition, machine learning, and digital twin technologies. The overarching goal is to develop real-time predictive models that enhance process efficiency and support intelligent decision-making in mineral beneficiation.

The work contributes to solving a major challenge in the mining industry: managing variability in feed material properties and translating complex particle–medium interactions into actionable process intelligence.

What we offer

• The support of an experienced and enthusiastic team of people, where you can share your expertise and grow as an expert.
• Remote work opportunities. Read more about other staff benefits.
• Work-life balance
• Development and career options of the big organisation.
• Work that matters! Read more about working with us.
• Finland is one of the most livable countries in the world, with a high quality of life, safety, an excellent education system, and a competitive economy. Read more about living in Oulu! 

Who are you?

In order to succeed and enjoy the position, we expect from you:

• Ongoing Master’s studies in any of the following fields: Process Engineering, Chemical Engineering, Mineral Processing, Industrial Automation.
• Basic understanding of froth flotation or mineral processing principles (or willingness to learn)
• Be able to use programming languages like Python. Familiarity with machine learning frameworks.
• Documentation & Reporting (maintain detailed experimental records, code documentation, and system diagrams. Thesis-related documentation)
• Fluent in spoken and written English abilities

In addition, having one or more of the following knowledge areas is advantageous:

• Sensor Integration & Experimental work (online and offline sensors, multi-sensor data acquisition, troubleshooting)
• Data Engineering & Analytics (pipelines for automated data acquisition, storage, synchronization, feature extraction from process conditions)
• Machine Learning & Computational Modelling (algorithms for data-driven information retrieval, integration of machine learning models with digital twin platforms)

Control & Engineering design support (designing process control strategies, collaborating with project research team)

Salary

The position is fixed-term (6 months), starting on 01.05.2026 (or as soon as possible thereafter).

The salary will be based on the levels OV01 of the demand level chart for other experts and support staff of Finnish universities. In addition, a salary component based on personal work performance will be paid (maximum of 50 % of the job-specific component). Starting gross salary will be approximately. 2300-2600 EUR per month (before taxes). A trial period of 3 months is applied to the position. 

How to apply?

Interested? If yes, please apply by 15.04.2026 through our recruitment system. Please attach:

• Cover letter
• CV

The eligible applicants fitting best in the profile expected for the position will be invited to an on-site or remote interview. All applicants will be notified during the selection process.

We welcome applicants from all backgrounds, such as people of different ages, genders, and linguistic, cultural, or minority groups.

Contact Information

If you have any further questions, please contact Dr Raul Mollehuara Canales, Raul.MollehuaraCanales@oulu.fi